Studies of Scheduling, Design, and Synthesis of Batch, Semi-Continuous, and Continuous Processes

这笔赠款为各种工艺操作中出现的调度、设计和综合问题的理论、算法和计算技术的开发提供资金。所制定的算法办法将提供一个系统的框架，用于确定在时间范围内将任务分配给不同的处理单元、每项任务产生的材料数量、每项任务的时间和持续时间以及现有处理单元的设计和能力。针对具有多个交货期需求的连续批处理过程的短期调度问题，提出了一种新的连续时间模型。研究一种新的间歇过程综合、设计和调度的数学建模和优化框架。这项研究将为不确定间歇过程的设计和调度提供一种新的方法。如果研究成功，这项研究的结果将在化工和制造过程的操作、设计和综合方面带来实质性的改进。基于调度、设计和综合问题的新的连续时间公式的优化框架将允许生产设施有效地处理广泛的产品，解决产品需求中的各种多个交货期，并考虑产品需求的变化以及工艺参数和成本的不确定性。理论和算法的发展将与工业案例研究相辅相成，并将导致为制造过程的调度和设计开发计算工具。

This grant provides funding for the development of theoretical, algorithmic and computational techniques for scheduling, design, and synthesis problems that arise in a variety of process operations. The developed algorithmic approaches will provide a systematic framework for the determination of the assignments of the tasks to the different process units during the time horizon, the amounts of material produced in each task, the timing and duration of each task, and the design and capacities of the available process units. A novel continuous-time formulation for the short-term scheduling of continuous and batch processes with multiple due date demands will be investigated. A new mathematical modeling and optimization framework for the simultaneous synthesis, design and scheduling of batch processes will be studied. A new approach for the design and scheduling of batch processes under uncertainty will be developed.If successful, the results of this research will lead into substantial improvements in the operation, design and synthesis of chemical and manufacturing processes. The optimization framework which is based on the novel continuous time formulation of scheduling, design and synthesis problems will allow for production facilities to handle efficiently a wide spectrum of products, to address a variety of multiple due dates in the product demands, and to account for variations in the product demands as well as uncertainties in the processing parameters and costs. The theoretical and algorithmic developments will be complemented with industrial case studies and will lead to the development of computational tools for the scheduling and design of manufacturing processes.